论文名称：Double rule learning in boosting
论文类型：期刊论文
发表刊物：INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL
收录刊物：SCIE
卷号：4
期号：6
页面范围：1411-1420
ISSN号：1349-4198
关键字：boosting; AdaBoost; machine learning; classification
摘要：Boosting is an effective methodology for classification problems. AdaBoost is the most successful boosting algorithm that solved many practical difficulties of the earlier boosting algorithms. In this paper, we propose an improvement of AdaBoost, called DR-AdaBoost, in which a double-rule learning technique is used for improving the performance of AdaBoost. The DR-AdaBoost algorithm is evaluated with some classification problems of the UCI repository and it is also applied to a natural language processing task, text chunking. All experimental results show DR-AdaBoost outperforms AdaBoost. The improvement is significant, especially for those classification problems in which features are relevant.
发表时间：2008-06-01